Review of Non-Technical Losses Identification Techniques
نویسندگان
چکیده
Illegally consumption of electric power, termed as non-technical losses for the distribution companies is one dominant factors all over world many years. Although there are some conventional methods to identify these irregularities, such physical inspection meters at consumer premises etc, but it requires large number manpower and time; then also does not seem be adequate. Now a days various algorithms have been developed that proposed in different research papers, detect losses. In this paper reviewed, their important features highlighted limitations identified. Finally, qualitative comparison identification presented based on performance, costs, data handling, quality control execution times. It can concluded graph-based classifier, Optimum-Path Forest algorithm both supervised unsupervised variants, yields most accurate result
منابع مشابه
MIDAS: Detection of Non-technical Losses in Electrical Consumption Using Neural Networks and Statistical Techniques
Datamining has become increasingly common in both the public and private sectors. A non-technical loss is defined as any consumed energy or service which is not billed because of measurement equipment failure or illintentioned and fraudulent manipulation of said equipment. The detection of non-technical losses (which includes fraud detection) is a field where datamining has been applied success...
متن کاملA Review of Fish Taxonomy Conventions and Species Identification Techniques
Taxonomists, ecologists, geneticists or researchers from other biological fields who wish to adopt fish as a constituent of their studies often become discouraged when they find that ichthyology is a complex subject. In fish-based studies, the failure to recognize fishes as distinct biological units can lead to wrong diagnosis. Hence, this review paper attempts to clarify and discuss the latest...
متن کاملLearning to Identify Non-Technical Losses with Optimum-Path Forest
In this work we have proposed an innovative and accurate solution for non-technical losses identification using the Optimum-Path Forest (OPF) classifier and its learning algorithm. Results in two datasets demonstrated that OPF outperformed the state of the art pattern recognition techniques and OPF with learning achieved better results for automatic nontechnical losses identification than recen...
متن کاملIdentification of Technical Journals by Image Processing Techniques
The emphasis of this study is put on developing an automatic approach to identifying a given unknown technical journal from its cover page. Since journal’s cover pages contain a great deal of information, determining the title of an unknown journal using optical character recognition techniques seems difficult. Comparing the layout structures of text blocks on the journals’ cover pages is an ef...
متن کاملReview of person re-identification techniques
Person re-identification across different surveillance cameras with disjoint fields of view has become one of the most interesting and challenging subjects in the area of intelligent video surveillance. Although several methods have been developed and proposed, certain limitations and unresolved issues remain. In all of the existing re-identification approaches, feature vectors are extracted fr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal on Recent and Innovation Trends in Computing and Communication
سال: 2021
ISSN: ['2321-8169']
DOI: https://doi.org/10.17762/ijritcc.v9i3.5457